Accelerating Spectrum Access in Cognitive Radio Networks via Social Analysis of Secondary Users

Sponsor: National Science Foundation (NSF)

Duration: January 2014 - December 2018

Investigators: Dr. Jiang (Linda) Xie (PI), Dr. Yu Wang (CS Dept.), and Dr. Yang Cao (Sociology Dept.)

Students: Ji Li, Xingya Liu, Hanshang Li, and Ting Li

Overview:

Cognitive radio has recently emerged as a promising technology to overcome the imbalance between the increase in spectrum access demand and the inefficiency in spectrum usage by allowing dynamic spectrum access. This research focuses on exploring the time, location, and spectrum-dependent social patterns of secondary users in a cognitive radio network in designing new fully distributed channel rendezvous, secure channel information exchange, and information propagation algorithms that guarantee rendezvous and minimize spectrum access delay in a practical dynamic spectrum environment.

This project is the first endeavor that systematically incorporates the social analysis of secondary users in spectrum access design under practical scenarios.

This research is interdisciplinary covering integrating advances in wireless network design, mobile user social property analysis, and social science research.

Research Activities and Key Outcomes:

The specific research goal to be accomplished in this project is to design, analyze, and evaluate fast and efficient spectrum access schemes for cognitive radio networks without a common control channel. The project has the following main research components:

• Social analysis of cognitive radio (CR) users: conduct a comprehensive study of social analysis on CR users at different levels: (1) individual level, (2) network level, and (3) population level.

• Fast channel rendezvous: (1) exploit location and channel information from the secondary user social graph and (2) design efficient channel hopping sequences for fast spectrum access.

• Accurate channel information exchange: (1) exploit the trustworthiness of the information from the secondary user social graph and (2) design distributed security assurance algorithms for fighting against false channel information exchange attacks to further enhance the spectrum access performance.

• Efficient channel information recommendation: (1) exploit the propagation structures from the social network analysis and (2) design social-aware propagation schemes for spectrum recommendation via social interactions.

Publications:

• Y. Liu, W. Quan, T. Wang, and Y. Wang, "Delay-constrained utility maximization for video Ads push in mobile opportunistic D2D networks," IEEE Internet of Things Journal, vol. 5, no. 5, pp. 4088-4099, October 2018.

• Y. Zhan, Y. Xia, J. Zhang, and Y.Wang, "Incentive mechanism design in mobile opportunistic data collection with time sensitivity," IEEE Internet of Things Journal,, vol. 5, no. 1, pp. 246-256, February 2018.

• F. Li, Z. Li, K. Sharif, Y. Liu, and Y. Wang, "Multi-layer-based opportunistic data collection in mobile crowdsourcing networks," World Wide Web (Springer), vol. 21, no. 3, pp. 783-802, May 2018.

• B. Guo, H. Chen, Q. Han, Z. Yu, D. Zhang, and Y. Wang, "Worker-contributed data utility measurement for visual crowdsensing systems," IEEE Transactions on Mobile Computing, vol. 16, no. 8, pp. 2379-2391, 2017.

• F. Li, C. Tian, T. Li, and Y. Wang, "Energy efficient social routing framework for mobile social sensing networks," Tsinghua Science and Technology, vol. 21, no. 4, pp. 363-373, August 2016.

• Y. Liu, F. Li, and Y. Wang, "Incentives for delay-constrained data query and feedback in mobile opportunistic crowdsensing," Sensors, vol. 16, no. 7, 2016.

• F. Li, Z. Yin, S. Tang, Y. Cheng, and Y. Wang, ""Optimization problems in throwbox-assisted delay tolerant networks: Which throwboxes to activate? How many active ones I need?," IEEE Transactions on Computers, vol. 65, no. 5, pp. 1663-1670, April 2016.

• Y. Zhu, C. Zhang, X. Mao and Y. Wang, "Social based throwbox placement schemes for large-scale mobile social delay tolerant networks," Computer Communications, vol. 65, pp. 10-26, July 2015.

• F. Li, S. Chen, M. Huang, Z. Yin, C. Zhang, and Y. Wang, "Reliable topology design in time-evolving delay-tolerant networks with unreliable links," IEEE Transactions on Mobile Computing, vol. 14, no. 6, pp. 1301-1314, June 2015.

• T. Samak, J. Xie, and X. Liu, "Multi-destination rendezvous in cognitive radio networks," Proc. IEEE International Conference on Communications (ICC 2018), April 2018.

• X. Liu and J. Xie, "A 2D heterogeneous rendezvous protocol for multi-wideband cognitive radio networks," Proc. IEEE Infocom,, May 2017.

• W. Li, F. Li, K. Sharif, and Y. Wang, "When user interest meets data quality: A novel user filter scheme for mobile crowd sensing," Proc. IEEE International Conference on Parallel and Distributed Systems (ICPADS),, December 2017.

• X. Liu and J. Xie, "A self-adaptive optimal fragmentation protocol for multi-channel cognitive radio ad hoc networks," Proc. IEEE Global Communications Conference (GLOBECOM),, December 2016.

• T. Li, T. Jung, H. Li, L. Cao, W. Wang, X.-Y. Li, and Y. Wang, "Scalable privacy-preserving participant selection in mobile crowd sensing," Proc. IEEE International Conference on Pervasive Computing and Communications (PerCom),, 2017.

• H. Li, T. Li, F. Li, W. Wang, and Y. Wang, "Enhancing participant selection through caching in mobile crowd sensing," Proc. International Symposium on Quality of Service (IWQoS 2016),, June 2016.

• X. Liu and J. Xie, "SUBSET: A joint design of channel selection and channel hopping for fast blind rendezvous in cognitive radio ad hoc networks," Proc. IEEE International Conference on Sensing, Communication, and Networking (SECON),, pp. 426-434, June 2015.

• H. Li, T. Li, and Y. Wang, "Dynamic participant recruitment of mobile crowd sensing for heterogeneous sensing tasks," Proc. IEEE International Conference on Mobile Ad hoc and Sensor Systems (MASS),, October 2015.

• Y. Zhu, C. Zhang, F. Li, and Y. Wang, "Geo-social: Routing with location and social metrics in mobile opportunistic networks," Proc. IEEE International Conference on Communications (ICC),, June 2015.

• X. Liu and J. Xie, "A practical self-adaptive rendezvous protocol in cognitive radio ad hoc networks," Proc. IEEE Infocom,, pp. 2085-2093, April 2014.

• L. Jiang, F. Li, C. Tian, L. Zhu, and Y. Wang, "Closeness-based routing with temporal constraint for mobile social delay tolerant networks," Proc. IEEE Global Telecommunications Conference (GLOBECOM),, December 2014.

• C. Tian, F. Li, L. Jiang, Z. Wang, and Y. Wang, "Energy efficient social-based routing for delay tolerant networks," Proc. International Conference on Wireless Algorithms, Systems and Applications (WASA),, June 2014.

• Y. Zhu, C. Zhang, and Y. Wang, "Social based throwbox placement in large-scale throwbox-assisted delay tolerant networks," Proc. IEEE International Conference on Communications (ICC),, June 2014.

• F. Li, Z. Yin, S. Tang, C. Zhang, Y. Cheng, and Y. Wang, "k-throwbox placement problem in throwbox-assisted delay tolerant networks," Proc. IEEE Global Telecommunications Conference (GLOBECOM),, December 2014.

Broader Impact:

This project will have a significant impact on efficient spectrum access. With the active involvement of industrial companies and standard working groups on cognitive radio products and dynamic spectrum access regulatory policies, social analysis of CR users is a critical component to further enhance spectrum access efficiency and accelerate cognitive radio network deployment. Unfortunately, they have not been adequately explored in existing research and development.

This research will generate innovative techniques to serve numerous applications of the cognitive radio technology, e.g., public safety networks, emergency networks, health monitoring, and cognitive mesh networks. It will also have significant impacts on research in emerging technologies with dynamic spectrum access, such as vehicular networks, mobile health, and opportunistic interconnections of heterogeneous wireless networks. It will also greatly advance the understanding of social interactions of mobile users in wireless networks.

Education Activities:

• Curriculum Enhancement: research results on cognitive radio, mobile sensing, and social analysis from this research are incorporated into the graduate-level courses.

• Graduate Student Mentoring: four PhD students have worked on the research of this project. All of them have graduated with PhD degrees.